# KeyError(f"None Of [{key}] Are In The [{axis_name}]") When Calculating Average Metrics After Cross Validation

## 04 January 2022 - 1 answer

I am trying to calculate some average metrics after performing cross validation. The function that do that is the following one:

``````from sklearn.model_selection import KFold
from numpy import mean
from numpy import std
from sklearn.metrics import confusion_matrix
from sklearn.linear_model import LogisticRegression

# Returns average confusion matrix, average accuracy
# and average standard deviation after all the cross-validation runs
def get_average_metrics(model,cv,X_fss,y):
conf_matrix_list_of_arrays = []
scores = []
for train_index, test_index in cv.split(X_fss):
X_train, X_test = X_fss[train_index], X_fss[test_index]
y_train, y_test = y[train_index], y[test_index]
score = model.fit(X_train, y_train).score(X_test, y_test)
conf_matrix = confusion_matrix(y_test, model.predict(X_test))
scores.append(score)
conf_matrix_list_of_arrays.append(conf_matrix)
# Average confusion matrix
mean_of_conf_matrix_arrays = mean(conf_matrix_list_of_arrays, axis=0)
# Average accuracy
avg_score = mean(scores)
# Average standard deviation
std_score = std(scores)
return avg_score,std_score,mean_of_conf_matrix_arrays
``````

However, I get this error in `X_train, X_test = X_fss[train_index], X_fss[test_index]` line:

KeyError: "None of [Int64Index([ 1, 2, 4, 5, 6, 7,
9, 10, 11, 12,\n ...\n 1620, 1621, 1622, 1623, 1624, 1625, 1626, 1627, 1629, 1630],\n dtype='int64', length=1467)] are in the [columns]"

• model -> `logistic = LogisticRegression()`
• cv -> `cv = KFold(n_splits=10,shuffle=True, random_state=1)`
• X_fss -> a Dataframe of size (1631, 4)
• y -> a Series of size (1631,)

`X_fss` sample: `y` sample: I have solved it converting `X_fss`Dataframe into a numpy array:
``````X_fss = X_fss.to_numpy()